DIAGNOSIS OF SENILE ASTHENIA USING THE EDMONTON FRAIL AND FRAILTY PHENOTYPE QUESTIONNAIRE IN PATIENTS WITH ACUTE CHOLECYSTITIS
Bibliographic record
Abstract
Summary. About 80 million surgical interventions are performed annually in Europe, and according to the observations of the National Centre for Statistics of Germany, about a third of them are performed in patients over 65 years of age. The syndrome of senile asthenia is of particular concern as one of the factors influencing the general condition of the patient and the course of the perioperative period. Objective: to compare the effectiveness of the diagnosis of senile asthenia using the Edmonton Frail and Frailty Phenotype Questionnaire scales in patients with emergency abdominal surgical pathology. Materials and methods. To compare the effectiveness of the diagnosis of senile asthenia using the Edmonton Frail and Frailty Phenotype Questionnaire scales in emergency abdominal surgery, we analysed the results of treatment of 80 (100.0%) elderly and senile patients with acute cholecystitis in the setting of cholelithiasis. Results and discussion. The syndrome of senile asthenia has a great impact on the perioperative period. Early detection of the syndrome with the help of scales allows modifying perioperative treatment and reducing the number of postoperative complications in this group of patients. Therefore, the definition of a scale that can be used to quickly and accurately assess the syndrome of senile asthenia is of great importance for emergency surgical care of elderly and senile patients. Conclusions. The use of scales for the assessment of senile asthenia allows predicting the course of the perioperative period in patients with emergency surgical pathology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".